The rapid evolution of autonomous Artificial Intelligence (AI) systems has introduced complex ethical, legal, and managerial challenges for modern business governance. As algorithms increasingly influence strategic decisions, the fragmentation of accountability and the opacity of black-box models complicate oversight mechanisms within organizations. Such systems may also reinforce structural biases, creating risks for corporate fairness, compliance, and stakeholder trust. Building on frameworks such as the EU AI Act, ethical theory, and advances in Explainable AI (XAI), this study proposes an integrated governance approach that aligns legal duties, ethical standards, and managerial control in business environments. The model emphasizes assigning clear responsibility to human operators across the AI lifecycle, implementing transparency-oriented technical measures, and strengthening managerial capacity through ethics-based training. The findings suggest that embedding responsible AI principles into corporate decision-making can enhance risk management, support sustainable value creation, and ensure that autonomous systems contribute to socially equitable and accountable business practices
Artificial Intelligence (AI), Accountability, Transparency, Bias, Human Oversight, business management
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